• DocumentCode
    419712
  • Title

    WillHunter: interactive image retrieval with multilevel relevance

  • Author

    Wu, Hong ; Lu, Hanqing ; Ma, Songde

  • Author_Institution
    Nat. Lab. of Pattern Recognition, Chinese Acad. of Sci., China
  • Volume
    2
  • fYear
    2004
  • fDate
    23-26 Aug. 2004
  • Firstpage
    1009
  • Abstract
    Relevance feedback has become a key component in CBIR system. Although most current relevance feedback approaches are based on dichotomous relevance measurement, this coarse measurement is a distortion of the reality. We study relevance feedback with multi-level relevance measurement to better identify the u ser needs and preferences. To validate the use of multi-level relevance measurement and our relevance feedback algorithm, we developed a CBIR prototype system - WillHunter. There are two novelties in our system, one is our SVM-based fast learning algorithm; another is the easy-to-use graphical user interface, especially the relevance-measuring instrument. Not only experiments are conducted to assess the algorithm, but also usability study is carried out to evaluate the user interface.
  • Keywords
    content-based retrieval; graphical user interfaces; image retrieval; relevance feedback; support vector machines; SVM-based fast learning algorithm; WillHunter; content-based image retrieval; dichotomous relevance measurement; graphical user interface; interactive image retrieval; relevance feedback; Current measurement; Distortion measurement; Feedback; Image retrieval; Information science; Instruments; Pattern recognition; Prototypes; Usability; User interfaces;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
  • ISSN
    1051-4651
  • Print_ISBN
    0-7695-2128-2
  • Type

    conf

  • DOI
    10.1109/ICPR.2004.1334430
  • Filename
    1334430